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- W2032256633 abstract "In this paper, a novel edge-oriented neural-network-based adaptive interpolation scheme for natural image is proposed. An image analysis module is used to classify pixels of the input image into non-oriented class and oriented class. The bilinear interpolation is used to interpolate the non-oriented regions and a neural network is proposed to interpolate the oriented regions. High-resolution digital images along with supervised learning algorithms can be used to automatically train the proposed neural network. Simulation results demonstrate that the proposed new resolution enhancement algorithm can produce higher visual quality of the interpolated image than the conventional interpolation methods." @default.
- W2032256633 created "2016-06-24" @default.
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- W2032256633 date "2002-10-01" @default.
- W2032256633 modified "2023-10-09" @default.
- W2032256633 title "A NEURAL-NETWORK-BASED IMAGE RESOLUTION ENHANCEMENT SCHEME FOR IMAGE RESIZING" @default.
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- W2032256633 doi "https://doi.org/10.1142/s0219467802000780" @default.
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